Attitudes Of Chinese Cancer Patients Toward The Clinical Use Of Artificial Intelligence

被引:37
作者
Yang, Keyi [1 ]
Zeng, Zhi [1 ]
Peng, Hu [1 ]
Jiang, Yu [1 ]
机构
[1] Sichuan Univ, Canc Ctr, Dept Head & Neck Oncol, West China Hosp, 37 Guo Xue Lane, Chengdu 610041, Sichuan, Peoples R China
来源
PATIENT PREFERENCE AND ADHERENCE | 2019年 / 13卷
关键词
artificial intelligence; attitude; cancer; cancer patient; clinical use; oncology; OUTCOMES;
D O I
10.2147/PPA.S225952
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Purpose: Artificial intelligence (AI) plays a substantial role in many domains, including medical fields. However, we still lack evidence to support whether or not cancer patients will accept the clinical use of AI. This research aims to assess the attitudes of Chinese cancer patients toward the clinical use of artificial intelligence in medicine (AIM), and to analyze the possible influencing factors. Patients and methods: A questionnaire was delivered to 527 participants. Targeted people were Chinese cancer patients who were informed of their cancer diagnosis. Results: The effective response rate was 76.3% (402/527). Most cancer patients trusted AIMs in both stages of diagnosis and treatment, and participants who had heard of AIMs were more likely to trust them in the diagnosis phase. When an AIM's diagnosis diverged from a human doctor' s, ethnic minorities, and those who had received traditional Chinese medicine (TCM), had never received chemotherapy, were more likely to choose "AIM", and when an AIM's therapeutic advice diverged from a human doctor's, male participants, and those who had received TCM or surgery, were more likely to choose "AIM". Conclusion: Most Chinese cancer patients believed in the AIM to some extent. Nevertheless, most still thought that oncology physicians were more trustworthy when their opinions diverged. Participants' gender, race, treatment received, and AIM related knowledge might influence their attitudes toward the AIM. Most participants thought AIM would assist oncology physicians in the future, while little really believed that oncology physicians would completely be replaced.
引用
收藏
页码:1867 / 1875
页数:9
相关论文
共 31 条
  • [1] User acceptance of an app-based adherence intervention: Perspectives from patients taking oral anticancer medications
    Ali, Eskinder Eshetu
    Chan, Sharlene Si Ling
    Leow, Jo Lene
    Chew, Lita
    Yap, Kevin Yi-Lwern
    [J]. JOURNAL OF ONCOLOGY PHARMACY PRACTICE, 2019, 25 (02) : 390 - 397
  • [2] [Anonymous], GUANGDONG MED J
  • [3] [Anonymous], IBM SURVEY CEE CITIZ
  • [4] [Anonymous], CHINA PUBLISHING J
  • [5] [Anonymous], SWETLITZ I IBMS WATS
  • [6] [Anonymous], GOV U IND RES ROUNDT
  • [7] [Anonymous], CONTIN MED ED
  • [8] Classification of breast cancer histology images using Convolutional Neural Networks
    Araujo, Teresa
    Aresta, Guilherme
    Castro, Eduardo
    Rouco, Jose
    Aguiar, Paulo
    Eloy, Catarina
    Polonia, Antonio
    Campilho, Aurelio
    [J]. PLOS ONE, 2017, 12 (06):
  • [9] Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer
    Bejnordi, Babak Ehteshami
    Veta, Mitko
    van Diest, Paul Johannes
    van Ginneken, Bram
    Karssemeijer, Nico
    Litjens, Geert
    van der Laak, Jeroen A. W. M.
    [J]. JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 2017, 318 (22): : 2199 - 2210
  • [10] How do ethnic minority patients experience the intercultural care encounter in hospitals? A systematic review of qualitative research
    Degrie, Liesbet
    Gastmans, Chris
    Mahieu, Lieslot
    de Casterle, Bernadette Dierckx
    Denier, Yvonne
    [J]. BMC MEDICAL ETHICS, 2017, 18 : 1 - 17